Two suspects from the 3.3.0 slowdown investigation had no signal. Both were
already computing the numbers and throwing them away, so this exposes them
rather than adding measurement.
Per-sweep heap trim. The trim runs after every cache sweep, and its cost
scales with resident heap, so it is the leading explanation for a node with
a populated database syncing slower than a fresh one. The report already
carried duration, fault deltas and reclaimed pages, but the whole
measurement sat behind a debug-journal check, so an ordinary node measured
nothing, and the call site discarded the result. The measurement now always
runs and only the log line stays gated. Records trim duration, minor faults
and reclaimed kilobytes. Measured cost of the always-on path is about six
microseconds per sweep against a trim costing milliseconds, at a cadence of
ten to a hundred and twenty seconds.
Honest limit, stated in the runbook: the fault delta spans only the trim
call, so it shows the trim itself faulting but not the faults that follow as
caches refill. The duration is the signal to correlate against sweep-job
queueing.
Rotation writes. Rotation copies archive-served reads forward and re-stores
nodes missing from both backends, both of which compete with sync I/O and
only happen on a populated online_delete database. The copy-forward count
existed but was reset by the rotation's own log line, so a metric reading it
would drop to zero on every swap; a never-reset total sits beside it now.
The re-store count was not measured at all. Rotation duration is
deliberately not recorded: the health throttle sleeps at eight points inside
the sequence and dominates exactly when the node is unhealthy, so the number
would conflate work with waiting.
Nothing added for the other two suspects. Get-object serving is already
covered by the handler label, the lookup histogram and the deferred and
saturation gauges; peer churn by the disconnect-reason counter.
Also replaces nine per-file cspell ignores with one ignoreRegExpList entry
for the telemetry macro names, and picks up the levelization baseline for the
consensus span-name test.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Slowness on the peer object-fetch path could be observed but not
attributed. Job duration metrics carry only `job_type`, and both
`RcvGetLedger` and `RcvGetObjByHash` report as `ledgerRequest`, so a
queue-wait spike could not be traced to a handler. Nothing measured
NodeStore cost, request size, or the differential charge.
Latency now decomposes into three additive parts, each separately
measurable:
end-to-end = queue wait + NodeStore lookup + everything else
- `handler` label on job_queued_total/_started_total/_finished_total and
job_queued_us/job_running_us. The value is sanitised: a name passes
through only if non-empty and all ASCII letters, else "other". Two job
names embed a ledger sequence, so a raw label would mint one series
per ledger; the rule bounds the domain at 43 names plus "other".
- getobject_lookup_us, _request_objects, _lookups_total{result},
_rejected_total{reason} and _charge, recorded at their call sites.
All three histograms get explicit bucket views: the SDK default stops
at 10,000, which every one of them exceeds.
- Per-job-type waiting/running/deferred gauges for the 35 non-special
job types. `deferred` is the leading indicator, since addJob never
rejects -- it defers, so backpressure otherwise shows up only as
latency after the fact.
`JobQueue::collect()` snapshots the counters under the queue lock and
publishes gauges after releasing it. Writing them while holding the lock
would invert a lock order against the collector's own lock, which the
collector's flush thread already holds when it calls this hook.
Tests assert exact values, including that the charge is priced on the
requested count rather than the capped iteration count.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
